Differential binding of the three PURA HeLa iCLIPs - 7: 2 oe vs 2 oe
1 Input
Show code
Dataset: oe_oe
Object of class BSFDataSet
#N Ranges: 147,893
Width ranges: 5
#N Samples: 4
#N Conditions: 2 Show code
# gene annotation
annotation <- readRDS("~/PURA/Molitor-et-al-2022/annotation.rds")
anno_txdb <- makeTxDbFromGRanges(annotation)
gns = genes(anno_txdb)
gns$gene_id = sub("\\..*", "", gns$gene_id)
idx = match(gns$gene_id, annotation$gene_id)
elementMetadata(gns) = cbind(elementMetadata(gns), elementMetadata(annotation)[idx,])
names(gns) = sub("\\..*", "", names(gns))
meta = data.frame(gene_id = gns$gene_id, gene_name = gns$gene_name, gene_type = gns$gene_type)
mcols(gns) = meta
gns$geneID = names(gns)
cdseq = cds(anno_txdb)
intrns = unlist(intronsByTranscript(anno_txdb))
utrs3 = unlist(threeUTRsByTranscript(anno_txdb))
utrs5 = unlist(fiveUTRsByTranscript(anno_txdb))
trl = GRangesList(CDS = cdseq, Intron = intrns, UTR3 = utrs3, UTR5 = utrs5)
# saveRDS(trl, paste0(outpath, "transcript_region_list_test.rds"))2 Assign genes and regions
Show code
bds <- assignToGenes(bds, anno.genes = gns, overlaps = "frequency")
# saveRDS(bds, paste0(outpath, "bds_test.rds"))
#bds <- assignToTranscriptRegions(bds, anno.transcriptRegionList = trl, overlaps.rule = c("UTR3", "UTR5", "CDS", "Intron"))
# bds <- assignToTranscriptRegions(bds, anno.transcriptRegionList = trl, overlaps = "frequency")
# getRanges(bds)3 Calculate background
Show code
4 Caluclate Changes
5 Changes
5.1 binding changes
5.2 background changes
Number of binding sites: 146993
Number of sig changing binding sites: 4
Number of sig changing background: 0
5.3 binding vs background changes
6 Save file
Show code
# rds
saveRDS(bs, paste0(outpath, "merged_bs_diff_oe_2v2_res.rds"))
# beds
# up_bs <- bs |> subset((bs$bs.padj < 0.01) & (bs$bs.log2FoldChange > 0)) |>
# makeGRangesFromDataFrame(.)
#
# down_bs <- bs |> subset((bs$bs.padj < 0.01) & (bs$bs.log2FoldChange < 0))|>
# makeGRangesFromDataFrame(.)
#
# up_bg <- bs |> subset((bs$bg.padj < 0.01) & (bs$bg.log2FoldChange > 0)) |>
# makeGRangesFromDataFrame(.)
#
# down_bg <- bs |> subset((bs$bg.padj < 0.01) & (bs$bg.log2FoldChange < 0))|>
# makeGRangesFromDataFrame(.)
#
# rtracklayer::export.bed(up_bs, paste0("merged_bs_upbs_oevsflag.bed"))
# rtracklayer::export.bed(down_bs, paste0("merged_bs_downbs_oevsflag.bed"))
# rtracklayer::export.bed(up_bg, paste0("merged_bs_upbg_oevsflag.bed"))
# rtracklayer::export.bed(down_bg, paste0("merged_bs_downbg_oevsflag.bed"))7 Session info
R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.3 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] ggpointdensity_0.1.0 GenomicFeatures_1.54.1 AnnotationDbi_1.64.0
[4] Biobase_2.62.0 dplyr_1.1.3 BindingSiteFinder_2.0.0
[7] GenomicRanges_1.54.1 GenomeInfoDb_1.38.0 IRanges_2.36.0
[10] S4Vectors_0.40.1 BiocGenerics_0.48.1 ggplot2_3.4.4
[13] knitr_1.44
loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 rstudioapi_0.15.0
[3] jsonlite_1.8.7 shape_1.4.6
[5] magrittr_2.0.3 ggbeeswarm_0.7.2
[7] farver_2.1.1 rmarkdown_2.24
[9] GlobalOptions_0.1.2 BiocIO_1.12.0
[11] zlibbioc_1.48.0 vctrs_0.6.3
[13] Cairo_1.6-1 memoise_2.0.1
[15] Rsamtools_2.18.0 RCurl_1.98-1.13
[17] webshot_0.5.5 htmltools_0.5.6
[19] S4Arrays_1.2.0 progress_1.2.2
[21] distributional_0.3.2 curl_5.0.2
[23] SparseArray_1.2.0 htmlwidgets_1.6.2
[25] plyr_1.8.9 cachem_1.0.8
[27] GenomicAlignments_1.38.0 lifecycle_1.0.3
[29] iterators_1.0.14 pkgconfig_2.0.3
[31] Matrix_1.6-1 R6_2.5.1
[33] fastmap_1.1.1 GenomeInfoDbData_1.2.11
[35] MatrixGenerics_1.14.0 clue_0.3-65
[37] digest_0.6.33 colorspace_2.1-0
[39] DESeq2_1.42.0 RSQLite_2.3.2
[41] labeling_0.4.3 filelock_1.0.2
[43] fansi_1.0.4 httr_1.4.7
[45] polyclip_1.10-6 abind_1.4-5
[47] compiler_4.3.1 bit64_4.0.5
[49] withr_2.5.0 doParallel_1.0.17
[51] BiocParallel_1.36.0 viridis_0.6.4
[53] DBI_1.1.3 ggforce_0.4.1
[55] biomaRt_2.58.0 MASS_7.3-60
[57] rappdirs_0.3.3 DelayedArray_0.28.0
[59] rjson_0.2.21 tools_4.3.1
[61] vipor_0.4.5 beeswarm_0.4.0
[63] glue_1.6.2 restfulr_0.0.15
[65] grid_4.3.1 cluster_2.1.4
[67] generics_0.1.3 gtable_0.3.4
[69] tidyr_1.3.0 hms_1.1.3
[71] xml2_1.3.5 utf8_1.2.3
[73] XVector_0.42.0 foreach_1.5.2
[75] pillar_1.9.0 ggdist_3.3.0
[77] stringr_1.5.0 circlize_0.4.15
[79] tweenr_2.0.2 BiocFileCache_2.10.1
[81] lattice_0.21-8 rtracklayer_1.62.0
[83] bit_4.0.5 tidyselect_1.2.0
[85] locfit_1.5-9.8 ComplexHeatmap_2.18.0
[87] Biostrings_2.70.1 gridExtra_2.3
[89] SummarizedExperiment_1.32.0 svglite_2.1.2
[91] xfun_0.40 matrixStats_1.0.0
[93] stringi_1.7.12 yaml_2.3.7
[95] kableExtra_1.3.4 evaluate_0.21
[97] codetools_0.2-19 tibble_3.2.1
[99] cli_3.6.1 systemfonts_1.0.4
[101] munsell_0.5.0 Rcpp_1.0.11
[103] dbplyr_2.4.0 png_0.1-8
[105] XML_3.99-0.15 ggrastr_1.0.2
[107] parallel_4.3.1 blob_1.2.4
[109] prettyunits_1.1.1 bitops_1.0-7
[111] viridisLite_0.4.2 scales_1.2.1
[113] purrr_1.0.2 crayon_1.5.2
[115] GetoptLong_1.0.5 rlang_1.1.1
[117] KEGGREST_1.42.0 rvest_1.0.3